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Science. 2017 Dec 1;358(6367). pii: eaan4368. doi: 10.1126/science.aan4368.

The target landscape of clinical kinase drugs.

Author information

1
Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Germany.
2
German Cancer Consortium (DKTK), Heidelberg, Germany.
3
German Cancer Research Center (DKFZ), Heidelberg, Germany.
4
Department of Internal Medicine III, University Hospital, Ludwig-Maximilians-Universität (LMU) München, Munich, Germany.
5
Department of Apoptosis in Hematopoietic Stem Cells, Helmholtz Center Munich, German Center for Environmental Health (HMGU), Munich, Germany.
6
Institut für Klinische Chemie und Pathobiochemie, TUM, Munich, Germany.
7
Oncology, Nerviano Medical Sciences Srl, Milan, Italy.
8
Research Unit Analytical Pathology, Helmholtz Zentrum München, Neuherberg, Germany.
9
SAP SE, Potsdam, Germany.
10
Department of Medicine III, Klinikum rechts der Isar, TUM, Munich, Germany.
11
Structural Bioinformatics Group, Charité-Universitätsmedizin, Berlin, Germany.
12
Institute of Surgical Pathology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
13
Center of Thoracic Surgery, Krefeld, Germany.
14
Estonian Genome Center, University of Tartu, Tartu, Estonia.
15
Tartu University Hospital, Tartu, Estonia.
16
SAP SE, Walldorf, Germany.
17
Department of Chemistry, TUM, Garching, Germany.
18
Center For Integrated Protein Science Munich (CIPSM), Munich, Germany.
19
Department of Pediatrics, Dr von Hauner Children's Hospital, LMU, Munich, Germany.
20
Chair of Proteomics and Bioanalytics, Technical University of Munich (TUM), Freising, Germany. kuster@tum.de.
21
Bavarian Biomolecular Mass Spectrometry Center (BayBioMS), TUM, Freising, Germany.

Abstract

Kinase inhibitors are important cancer therapeutics. Polypharmacology is commonly observed, requiring thorough target deconvolution to understand drug mechanism of action. Using chemical proteomics, we analyzed the target spectrum of 243 clinically evaluated kinase drugs. The data revealed previously unknown targets for established drugs, offered a perspective on the "druggable" kinome, highlighted (non)kinase off-targets, and suggested potential therapeutic applications. Integration of phosphoproteomic data refined drug-affected pathways, identified response markers, and strengthened rationale for combination treatments. We exemplify translational value by discovering SIK2 (salt-inducible kinase 2) inhibitors that modulate cytokine production in primary cells, by identifying drugs against the lung cancer survival marker MELK (maternal embryonic leucine zipper kinase), and by repurposing cabozantinib to treat FLT3-ITD-positive acute myeloid leukemia. This resource, available via the ProteomicsDB database, should facilitate basic, clinical, and drug discovery research and aid clinical decision-making.

PMID:
29191878
DOI:
10.1126/science.aan4368
[Indexed for MEDLINE]

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